This course runs for a duration of 4 Days.
The class will run daily from 9 AM ET to 5 PM ET.
Class Location: Virtual LIVE Instructor Led - Virtual Live Classroom.
This offering provides participants with introductory to advanced knowledge of metadata modeling concepts, and how to model metadata for predictable reporting and analysis results using Framework Manager. Participants will learn the full scope of the metadata modeling process, from initial project creation, to publishing of metadata to the web, enabling end users to easily author reports and analyze data.
Audience
Data Modelers
Objectives
Introduction to IBM Cognos Framework Manager
• Model data and identifying related data
• Define requirements and modeling strategies
• Overview of IBM Cognos Framework Manager
• Create a baseline project
• Extend a model
• Prepare reusable metadataModel for predictable results in IBM Cognos Framework Manager
• Identify query issues
• Identify reporting traps
• Model virtual star schemas
• Use query subjects, modify relationships, and consolidate metadata using virtual objects
• Create calculations, filter data, and customize metadata for runtime
• Implement a time dimension and specify determinantsModel for presentation in IBM Cognos
Framework Manager
• Create a presentation view
• Examine data source query subject types and stored procedure query subject types
• Specify data security and package security
• Specify object security and dynamic data security
• Create analysis objects
• Manage OLAP data sourcesAdvanced capabilities in IBM Cognos Framework Manager
• Explore SQL generation and the use of governors
• Examine the use of IBM Cognos SQL and generated SQL for DMR data
• Other query considerations
• Use session parameters, prompt macros, and security macro functions
• Use materialized views, minimize SQL, and enable Dynamic Query Mode (DQM)
• DQM, CQM, caching metadata, query processing, aggregate calculation, and other ways to improve performance
Extended capabilities in IBM Cognos Framework Manager (Optional)
• Perform basic maintenance and management on a model
• Remap metadata to another source and import and link additional data sources
• Run scripts to automate or update a model and report on a model
• Segment a project, link a project, and branch a model
• Nest packages and specify package languages and functions
• Explore additional modeling techniques and customize metadata for a multilingual audience
